Several control systems employed by vehicles, either autonomous vehicles or vehicles executing in autonomous-driving mode, predict future, safe motions, or paths, of the vehicle, both in order to avoid obstacles, such as other vehicles or pedestrians, but also to optimize some criteria associated to the operation of the vehicle. The target state can either be a fixed location, a moving location, a velocity vector, a region, or a combination thereof. The surroundings, such as road edges, pedestrians, and other vehicles, are sensed by the sensors of the vehicle and/or are at least partially known by a priori given information.
One of the tasks for controlling the autonomous or semi-autonomous vehicles executing in autonomous-driving mode automatically parks a vehicle into a parked position and orientation referred herein as a target state. The parking task can be formulated as the following. Given vehicle dynamics, a map of the parking space, an initial state representing the vehicle's start position and orientation, and a target state representing the vehicle's target parked position and orientation, determine a desired path or motion of the vehicle from the initial state to the target state and then control the actuators of the vehicle, e.g., vehicle's gas pedal and steering wheel, to ensure that the vehicle follows the desired path or motion. However, due to nonholonomic constraints on the motion of the vehicle and a typically narrow free space in the parking space, such as a parking garage or a parking lot, path planning for automatically parking a vehicle is challenging.
Most existing path planning solutions only cope with specific parking scenarios, or assume specific geometry of the parking space. For instance, a method described in U.S. Pat. No. 7,737,866 calculates paths for parallel parking and back-in parking. The method described in U.S. Pat. No. 8,497,782 assumes a special structure of the parking path, ignores obstacles, and calculates a path based on a specific geometry of the parking space. Also, the method described in U.S. Pat. No. 8,862,321 addresses parallel parking and requires the initial state of the vehicle to be within a so-called feasible starting region from which pre-coded parallel parking maneuvers is initiated. Although achieve real-time path generation, aforementioned methods restrict, more or less, the types of obstacles, the geometry of the parking space, and parking tasks, and fail to consider general parking scenarios.
Accordingly, there is a need for a system and a method for automatically parking a vehicle into a target space suitable for variety of real-life parking scenarios.